A Common Denominator: Calculating Hospitalization Rates for Ambulatory Care–Sensitive Conditions in California

Introduction Chronic health conditions are considered ambulatory care–sensitive conditions (ACSC) when the illness is controllable with effective and timely outpatient care that can potentially prevent the need for hospitalizations. Hospitalization rates for ACSC serve as an indicator of the access to and quality of primary care for chronic conditions. Standard methods to calculate hospitalization rates incorporate the total population in the denominator instead of the total population at risk for a hospitalization. By accounting for people with an ACSC, this study compares standard methods to a disease prevalence–adjusted method to highlight the importance of adjusting for ACSC prevalence when using ACSC hospitalizations in assessing primary care outpatient services. Methods We combined California Health Interview Survey and hospital discharge data to calculate standard (crude and age-adjusted) and disease prevalence-adjusted hospitalization rates for hypertension and congestive heart failure. To compare rate calculations, we ranked California counties by their hospitalization rate. Results Counties had high prevalence and low numbers of hospitalizations for hypertension; their rankings for hospitalization rates for hypertension did not vary, even after accounting for prevalence. In contrast, counties had low prevalence and high numbers of hospitalizations for congestive heart failure; their rankings varied substantially for congestive heart failure after accounting for prevalence. Conclusion Because the number of people diagnosed with an ACSC is rising and costs to treat these conditions are increasing, our findings suggest that more accurate measures of ACSC hospitalization rates are needed. Incorporating disease prevalence will contribute to ACSC research by improving the validity of hospitalization rates as a measure for quality of primary care services.


Introduction
Chronic health conditions are the leading cause of death and disability in the United States and are the largest component of health care costs (1,2). Some chronic health conditions are deemed ambulatory care-sensitive conditions (ACSC) because they are controllable with effective and timely outpatient care and disease management (3). Rates of ACSC hospitalizations are used by public health officials to measure accessibility and effectiveness of primary health care services (4)(5)(6) and to control health costs for ACSCs. The Agency for Healthcare Research and Quality (AHRQ) used hospital inpatient discharge data to develop a set of Prevention Quality Indicators (PQIs) to assess ACSC hospitalizations (7,8).
Common ways to report hospitalization rates include crude and age-adjusted rates (9,10). These rate calculations use the total number of people in a population. Crude rates often serve as a summary measure that captures the overall burden of hospitalizations in the total population (11). ACSCs may be confounded by individual demographic characteristics, such as age, that have a heightened risk for being hospitalized. Adjusting by these factors is a common way to remove differences caused by demographics instead of health systems when comparing different populations. The process of adjusting provides a hypothetical rate that would be observed in a population if, for example, the age distribution of the group were the same as the age distribution of the standard population (9).
In traditional rate calculations, we assume that the events such as hospitalizations (numerator) occur among the population at risk (denominator). When calculating hospitalization rates, the true at-risk population is limited to those who have an ACSC. By using the number of people who report being diagnosed with an ACSC in the denominator, we can calculate a disease prevalence-adjusted rate that should more accurately reflect potentially avoidable hospitalizations.
We assessed the value of incorporating disease prevalence into the denominator in hospitalization-rate calculations. Using California Health Interview Survey (CHIS) data and hospital discharge data, this study examines standard and disease prevalence-adjusted ACSC hospitalization rates for hypertension and congestive heart failure (CHF) among California adults. By comparing a disease prevalence-adjusted rate with standard-rate calculations, we hypothesized that prevalence-adjusted hospitalization rates would highlight areas with higher ACSC burden.

Methods
We combined population-based data from CHIS and hospitalization data from the

Rate calculations
We calculated crude, disease prevalence-adjusted, ageadjusted, and combined age-and prevalence-adjusted hospitalization rates for hypertension and CHF. Crude rates were calculated with number of hospitalizations in county as the numerator and total population in county as the denominator (9). For disease prevalence-adjusted rates, the total number of people reporting the ACSC in the county served as the denominator. We used the direct method to calculate the age-adjusted hospitalization rate. First, age-specific hospitalization rates were calculated for each age group using the total number of hospitalizations for a given age group as the numerator and the total number of people in the population for a given age group as the denominator (9,11). Second, age-specific weights were calculated for each age group to capture the frequency of people in the total population for each age group. By summing the product of the age-specific hospitalization rate with the age-specific weights, we obtained the age-adjusted hospitalization rate. To incorporate disease prevalence into this rate, the total number of people reporting the ACSC served as the denominator for the age-specific hospitalization rates. The 95% confidence intervals for each hospitalization rate were also calculated to account for sampling variation (Appendix B).
All rates were aggregated at the California county level and subcounty level for Los Angeles and San Diego counties. Hospitalization rates were expressed per 100,000 people in the population (for the crude and age-adjusted rates) or per 100,000 people reporting the ACSC in the population (for the disease prevalence-adjusted and age-and disease prevalence-adjusted rates). To compare across counties, age-adjusted and age-and disease prevalence-adjusted rates were standardized (ie, process of comparing counties) by using 2000 US Census population data (12). To compare different rate calculations, we ranked counties from lowest (rank of 1) to highest (rank of 55) by their hospitalization rate. Counties were then grouped into quintiles with group 1 representing areas with the lowest hospitalization rates (indicating better access to or quality of primary care) and group 5 representing areas with the highest rates (indicating the worst access to or quality of primary care).

Results
In this study, we compared hospitalization rates that do and do not incorporate disease prevalence. We first present disease prevalence, average number of hospitalizations per year, and age-specific rates. Next, age-adjusted and combined age-and disease prevalence-adjusted hospitalization rates are discussed. Results are presented separately for each ACSC.

Hypertension
The annual prevalence of hypertension was high (24.8%) ( Table 1). Despite high prevalence, the average number of hospitalizations was low (6,355 total statewide per year). Older adults showed the highest age-specific hospitalization rate for hypertension at 95 per 100,000 people aged 75 years or older compared with people aged 65 to 74 years (58 per 100,000), 45 to 64 years (30 per 100,000), and 18 to 44 years (7 per 100,000) ( Figure 1). After accounting for disease prevalence, the population at risk for hospitalizations became smaller, and thus the age-specific rates per 100,000 people were higher but followed the same age pattern ( Figure 1). In comparison with the age-specific rate, the age-and disease prevalence-specific rate among people aged 75 years or older was about 50% higher (154 per 100,000) among those who reported ever being diagnosed with hypertension compared with the total population. There was a low hospitalization rate of hypertension at 24 per 100,000 people (Table 1). After accounting for disease prevalence, the rate was 97 per 100,000 people who reported ever being diagnosed with hypertension. After adjusting for age, the rates were 25 for the age-adjusted rate and 82 for the age-and disease prevalence-adjusted rate. Comparing across county rankings, counties that ranked low for the age-adjusted rate also ranked low for the combined adjusted rate ( Table 2). A similar pattern emerged for counties that had high age-adjusted rates and high age-and prevalence-adjusted rates. Only 14 counties differed in group ranking by 1 position.

Congestive heart failure
The annual prevalence of CHF (1.6%) was much lower than the hypertension prevalence. In contrast, the average The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
number of hospitalizations was higher (65,389 per year) ( Table 1). Across age groups, the highest age-specific hospitalization rate appeared among adults aged 75 years or older (1,775 per 100,000) followed by adults aged 64 to 74 years (673 per 100,000) and 18 to 64 years (82 per 100,000) ( Figure 2). After adjusting for age and disease prevalence, the age-specific rates increased substantially because of the small prevalence of CHF in the total population. Both rates showed a similar pattern in age distribution ( Figure 2). The overall CHF hospitalization rate was 249 per 100,000 (Table 1). After accounting for disease prevalence, the overall rate jumped to 16,773 hospitalizations per 100,000 people who reported ever being diagnosed with CHF. The CHF hospitalization rate increased slightly from the crude rate of 249 to the age-adjusted rate of 270. The combined age-and prevalence-adjusted hospitalization rate was 10,633 per 100,000 people who reported ever being diagnosed with CHF. Accounting for age reduced the CHF hospitalization rate in the combined adjusted rate.
CHF rate comparisons show that the group rankings of 31 counties changed, and among them, 15 counties changed by 2 or more quintiles (Table 3). Of the 11 counties that ranked the best in the age-adjusted rates, 3 counties changed by at least 2 positions from age-adjusting to the combined age-and prevalence-adjusted rate. Los Angeles SPA 5 ranked in group 1, and Santa Barbara and Santa Clara only ranked in group 2 in the age-adjusted rates; all 3 of them ranked in group 5 in the age-and prevalence-adjusted rates. Most of the counties that ranked the worst for the age-adjusted rates remained ranked in group 4 or group 5 in the combined age-and prevalenceadjusted rates. Stanislaus County and Los Angeles SPA 1-Antelope Valley were the exceptions; they ranked in group 5 in the age-adjusted rate and rose to group 3 in the combined rate.

Discussion
This study examined the effect of incorporating disease prevalence into the denominator when calculating hospitalization rates for hypertension and CHF. CHF has a low prevalence in the overall population and a high hospitalization rate, and hypertension has a high prevalence in the overall population and a low hospitalization rate. After incorporating disease prevalence into the rate calculation beyond age adjusting, 31 counties were shifted to a new CHF group ranking, compared with only 14 counties that were shifted to a new hypertension group ranking.
Higher ACSC hospitalization rates indicate poor quality, uncoordinated care, or insufficient access to health care (7). Yet, the choice of rate calculation for ACSC hospitalizations can lead to different conclusions about the effectiveness of primary care services. Crude rates measure the overall burden of hospitalizations in a population; age-adjusted rates serve as a relative index of risk that roughly adjusts for age differentials in disease risk of the population (12). These standard rate calculations capture the whole population rather than a population that is truly at risk for hospitalizations and may underestimate the overall burden of preventable hospitalizations. With appropriate disease management and lifestyle modifications, hypertension and congestive heart failure (CHF) are chronic conditions that are largely controllable in outpatient settings. Yet, the complications of CHF are more common and evident than those for hypertension; CHF is the leading cause of hospitalization in California, especially among older adults (8,13).
Little change occurred when accounting for hypertension prevalence in the population at risk for a hospitalization.
Counties with high hospitalization rates, regardless of accounting for disease prevalence, continue to be critical areas for improving outpatient care for hypertension. These findings on hypertension refute our hypothesis that adjusting for disease prevalence would highlight areas of higher disease burden. Although overall hospitalization rates are low for hypertension, a 2010 California report showed a dramatic increase in hypertension The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
hospitalization rates from 1999 through 2008; the largest increase occurred from 2006 through 2008 (outside this study period) (8). Future studies should still consider disease prevalence in calculating hypertension hospitalization rates.
Hospitalizations for CHF may be more preventable.
After adjusting for disease prevalence, more than half of California counties changed group rankings. Furthermore, counties that reported lower group rankings by standard calculations switched to higher group rankings when adjusting for CHF prevalence. Areas such as SPA 5-West Area in Los Angeles County, Santa Barbara County, and Santa Clara County all shifted from low to high hospitalization rates. Although these are more affluent areas with high incomes and low poverty levels, the low rate of hospitalizations and high rate when adjusted for CHF prevalence may point to a higher tendency to hospitalize people with CHF. Factors such as low disease prevalence and large number of hospital beds may also fuel these hospitalization rates and thus create a hospital supply-induced care rather than a need-induced care. Although we cannot differentiate between supply-induced and need-induced care, these rate calculations are based on a patient's zip code of residence and not on referrals into an area with better hospitals. Further research is needed to explain the higher prevalence-adjusted hospitalization rates in these areas to help reduce preventable CHF hospitalizations.
This study has several limitations. First, disease prevalence is measured from a population-based survey, whereas hospitalizations are based on an administrative census count. The underdiagnosis of chronic conditions is well established from population-based surveys (14,15), and so CHIS's self-reported awareness of diagnosed hypertension and CHF may underestimate the true prevalence. The rates we calculate will therefore be somewhat inflated, but we do not expect any significant bias by county. Previous literature has indicated data limitations for hospitalization data, including poor quality control and overestimation of disease trends (16)(17)(18). California's OSHPD regularly conducts a series of audits to ensure validity of hospitalization data. If data reports do not meet error tolerance levels of less than 0.1%, OSHPD sends the data back to the hospital to be corrected (19). To address the potential overestimation by OSHPD, we limited hospital records to principal diagnosis of hypertension and CHF. Although we weighted the population-based CHIS data and examine variance of the hospitalization rates, sampling biases may limit the accuracy of the findings.
Second, hospitalization rates have been shown to vary widely by sex and race/ethnicity (20)(21)(22)(23)(24)(25). Because of low ACSC prevalence in some counties, it was difficult to obtain stable estimates if we stratified by more than 1 demographic characteristic. We chose to adjust by age because hospitalizations vary most widely between age groups, as evident from the age-specific rates. Third, categories for CHF generated small sample sizes that may lead to high variance when incorporating CHF disease prevalence into the denominator. This issue affects rate calculations most when we stratify by age groups at the county level. We attempted to reduce the variation by using pooled CHIS data across 3 years and imputing agespecific disease prevalence where sample sizes are too small to report.
The results from this study show that disease prevalence should be incorporated into ACSC research. Previous studies have included disease prevalence as a control variable in statistical analysis rather than incorporating disease prevalence into the hospitalization rate (23,(26)(27)(28)      The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. (Continued on next page)